The present disclosure relates to an information processing device, an object recognition method, a program, and a terminal device.
With the advancement of image recognition technology in recent years, it has become possible to recognize the position and attitude of an object in an image input from a camera, through matching of image feature quantities. One application of such object recognition is an AR (Augmented Reality) application. In the AR application, a variety of information (e.g., advertising information, navigation information, or information for games) can be displayed such that it is overlaid on an image of a building, a road, or other objects existing in the real world.
Reference 1 (David G. Lowe, “Distinctive Image Features from Scale-Invariant Keypoints”, the International Journal of Computer Vision, 2004) proposes a method called SIFT (Scale Invariant Feature Transform) for extracting feature quantities of an image, the method having increased robustness against noise in the image, changes in scale, and rotation. Reference 2 (Mustafa Oezuysal, “Fast Keypoint Recognition using Random Ferns”, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 32, Nr.3, pp. 448-461, March 2010) proposes a method called Random Ferns with a lower processing cost, the method being adapted to extract feature quantities of an image using a portable terminal with low processing performance or the like.